Division of Pharmacology, Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
Protein J. 2024 Aug;43(4):697-710. doi: 10.1007/s10930-024-10219-8. Epub 2024 Jul 16.
The interaction between vascular endothelial growth factor A (VEGFA) and VEGF receptor 1(VEGFR1) is a central focus for drug development in pathological angiogenesis, where aberrant angiogenesis underlies various anomalies necessitating therapeutic intervention. Identifying hotspots of these proteins is crucial for developing new therapeutics. Although machine learning techniques have succeeded significantly in prediction tasks, they struggle to pinpoint hotspots linked to angiogenic activity accurately. This study involves the collection of diverse VEGFA and VEGFR1 protein sequences from various species via the UniProt database. Electron-ion interaction Potential (EIIP) values were assigned to individual amino acids and transformed into frequency-domain representations using discrete Fast Fourier Transform (FFT). A consensus spectrum emerged by consolidating FFT data from multiple sequences, unveiling specific characteristic frequencies. Subsequently, the Stockwell Transform (ST) was employed to yield the hotspots. The Resonant Recognition Model (RRM) identified a characteristic frequency of 0.128007 with an associated wavelength of 1570 nm and RRM-ST identified hotspots for VEGFA (Human 36, 46, 48, 67, 71, 74, 82, 86, 89, 93) and VEGFR1 (Human 224, 259, 263, 290, 807, 841, 877, 881, 885, 892, 894, 909, 913, 1018, 1022, 1026, 1043). These findings were cross-validated by Hotspots Wizard 3.0 webserver and Protein Data Bank (PDB). The study proposes using a 1570 nm wavelength for photo bio modulation to boost VEGFA/VEGFR1 interaction in the condition that is needed. It also aims to reduce VEGFA/VEGFR2 interaction, limiting harmful angiogenesis in conditions like diabetic retinopathy. Also, the identified hotspots assist in designing agonistic or antagonistic peptides tailored to specific medical requirements with abnormal angiogenesis.
血管内皮生长因子 A (VEGFA) 和血管内皮生长因子受体 1 (VEGFR1) 之间的相互作用是病理性血管生成药物开发的核心关注点，在这种情况下，异常的血管生成是各种需要治疗干预的异常的基础。鉴定这些蛋白质的热点对于开发新的治疗方法至关重要。尽管机器学习技术在预测任务中取得了显著成功，但它们在准确确定与血管生成活性相关的热点方面仍存在困难。
本研究通过 UniProt 数据库从不同物种中收集了多种 VEGFA 和 VEGFR1 蛋白质序列。将电子-离子相互作用势能 (EIIP) 值分配给各个氨基酸，并使用离散快速傅里叶变换 (FFT) 将其转换为频域表示。通过合并来自多个序列的 FFT 数据，形成了一个共识谱，揭示了特定的特征频率。随后，使用斯托克韦尔变换 (ST) 得出热点。共振识别模型 (RRM) 确定了一个特征频率为 0.128007，对应的波长为 1570nm，RRM-ST 确定了 VEGFA（人 36、46、48、67、71、74、82、86、89、93）和 VEGFR1（人 224、259、263、290、807、841、877、881、885、892、894、909、913、1018、1022、1026、1043）的热点。
这些发现通过 Hotspots Wizard 3.0 网络服务器和蛋白质数据库 (PDB) 进行了交叉验证。该研究提出使用 1570nm 波长进行光生物调节，以增强需要时的 VEGFA/VEGFR1 相互作用。它还旨在减少 VEGFA/VEGFR2 相互作用，限制糖尿病性视网膜病变等情况下有害的血管生成。此外，鉴定出的热点有助于设计针对特定医疗需求的具有异常血管生成的激动剂或拮抗剂肽。
